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73 lines
2.5 KiB
73 lines
2.5 KiB
from functools import partial
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import pytest
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import torch
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import torch.multiprocessing as mp
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import colossalai
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from colossalai.gemini.chunk import ChunkManager
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from colossalai.tensor import ColoTensor, ColoTensorSpec, ProcessGroup
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from colossalai.testing import parameterize, rerun_if_address_is_in_use
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from colossalai.utils import free_port
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from tests.test_tensor.common_utils import debug_print
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CUDA_MEM_0 = {False: 512, True: 1024}
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CUDA_MEM_1 = {False: 0, True: 1024}
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CPU_MEM = {True: {True: 0, False: 0}, False: {True: 512, False: 0}}
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@parameterize('keep_gathered', [True, False])
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@parameterize('pin_memory', [True, False])
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def exam_chunk_memory(keep_gathered, pin_memory):
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pg = ProcessGroup()
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debug_print([0], "keep_gathered: {}, pin_memory: {}".format(keep_gathered, pin_memory))
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params = [ColoTensor(torch.rand(8, 8), spec=ColoTensorSpec(pg)) for _ in range(3)]
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config = {2: dict(chunk_size=128, keep_gathered=keep_gathered)}
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chunk_manager = ChunkManager(config)
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assert chunk_manager.total_mem['cpu'] == 0
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assert chunk_manager.total_mem['cuda'] == 0
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for p in params:
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chunk_manager.register_tensor(p, 'param', 2, pin_memory=pin_memory)
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chunk_manager.close_all_groups()
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assert chunk_manager.total_mem['cpu'] == CPU_MEM[keep_gathered][pin_memory]
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assert chunk_manager.total_mem['cuda'] == CUDA_MEM_0[keep_gathered]
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chunks = chunk_manager.get_chunks(params)
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for chunk in chunks:
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chunk_manager.access_chunk(chunk)
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assert chunk_manager.total_mem['cpu'] == CPU_MEM[keep_gathered][pin_memory]
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assert chunk_manager.total_mem['cuda'] == CUDA_MEM_0[True]
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for chunk in chunks:
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chunk_manager.release_chunk(chunk)
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assert chunk_manager.total_mem['cpu'] == CPU_MEM[keep_gathered][pin_memory]
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assert chunk_manager.total_mem['cuda'] == CUDA_MEM_0[keep_gathered]
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for chunk in chunks:
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chunk_manager.move_chunk(chunk, torch.device('cpu'))
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assert chunk_manager.total_mem['cpu'] == CPU_MEM[keep_gathered][True]
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assert chunk_manager.total_mem['cuda'] == CUDA_MEM_1[keep_gathered]
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def run_dist(rank, world_size, port):
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colossalai.launch(config={}, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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exam_chunk_memory()
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@pytest.mark.dist
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@pytest.mark.parametrize('world_size', [2])
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@rerun_if_address_is_in_use()
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def test_chunk_manager(world_size):
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run_func = partial(run_dist, world_size=world_size, port=free_port())
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mp.spawn(run_func, nprocs=world_size)
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if __name__ == '__main__':
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test_chunk_manager(2)
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